Eco-driving key factors that influence fuel consumption in heavy-truck fleets: A Colombian case

This research identifies key variables that influence fuel consumption that might be improved through eco-driving training programs under three circumstances that have been scarcely studied before: (a) heavy- and medium-duty truck fleets, (b) long-distance freight transport, and (c) the Latin American region. Based on statistical analyses that include multivariate regression of operational variables on fuel consumption, the impacts of an eco-driving training campaign were measured by comparing ex ante and ex post data. Operational variables are grouped into driving errors, trip conditions, driver behavior, driver profile, and vehicle attributes.The methodology is applied in a freight fleet with nationwide transport operations located in Colombia, where the steepness of its roads plays an important role in fuel consumption. The fleet, composed of 18 trucks, is equipped with state-of-the-art real-time data logger systems. During four months, 517 trips traveling a total distance of 292,512 km and carrying a total of 10,034 tons were analyzed.The results show a baseline average fuel consumption (FC) of 1.716 liters per ton-100 km. A different logistics performance indicator, which measures FC in liters per ton transported each 100 km, shows an average of 3.115. After the eco-driving campaign, reductions of 6.8% and 5.5% were obtained. Drivers’ experience, driving errors, average speed, and weight-capacity ratio, among others, were found to be highly relevant to FC. In particular, driving errors such as acceleration, braking and speed excesses are the most sensitive to eco-driving training, showing reductions of up to 96% on the average number of events per trip.     

Cost analysis for high-volume and long-haul transportation of densified biomass feedstock

Using densified biomass to produce biofuels has the potential to reduce the cost of delivering biomass to biorefineries. Densified biomass has physical properties similar to grain, and therefore, the transportation system in support of delivering densified biomass to a biorenery is expected to emulate the current grain transportation system. By analyzing transportation costs for products like grain and woodchips, this paper identifies the main factors that impact the delivery cost of densified biomass and quantifies those factors’ impact on transportation costs. This paper provides a transportation-cost analysis which will aid the design and management of biofuel supply chains. This evaluation is very important because the expensive logistics and transportation costs are one of the major barriers slowing development in this industry.Regression analysis indicates that transportation costs for densified biomass will be impacted by transportation distance, volume shipped, transportation mode used, and shipment destination, just to name a few. Since biomass production is concentrated in the Midwestern United States, a biorefinery’s shipments will probably come from that region. For shipments from the Midwest to the Southeast US, barge transportation, if available, is the least expensive transportation mode. If barge is not available, then unit trains are the least expensive mode for distances longer than 161 km (100 miles). For shipments from the Midwest to the West US, unit trains are the least expensive transportation mode for distances over 338 km (210 miles). For shorter distances, truck is the least expensive transportation mode for densified biomass.     

Carbon emission from urban passenger transportation in Beijing

Urban passenger transport significantly contributes to global greenhouse gas emissions, especially in developing countries owing to the rapid motorization, thus making it an important target for carbon reduction. This article established a method to estimate and analyze carbon emission from urban passenger transport including cars, rail transit, taxis and buses. The scope of research was defined based on car registration area, transport types and modes, the stages of rail transit energy consumption. The data availability and gathering were fully illustrated. A city level emission model for the aforementioned four modes of passenger transport was formulated, and parameters including emission factor of electricity and fuel efficiency were tailored according to local situations such as energy structure and field survey. The results reveal that the emission from Beijing’s urban passenger transport in 2012 stood at 15 million tonnes of CO₂, of which 75.5% was from cars, whereas car trip sharing constitutes only 42.5% of the total residential trips. Bus travel, yielding 28.6 g CO₂, is the most efficient mode of transport under the current situations in terms of per passenger kilometer (PKM) emission, whereas car or taxi trips emit more than 5 times that of bus trips. Although a decrease trend appears, Beijing still has potential for further carbon reduction in passenger transport field in contrast to other cities in developed countries. Development of rail transit and further limitation on cars could assist in reducing 4.39 million tonnes CO₂ emission.     

New car preferences move away from greater size,weight and power: Impact of Dutch consumer choices on average CO2-emissions

This paper assesses the separate effects of consumer preferences and technological advances on sales-weighted average CO₂ emissions of new passenger cars in the Netherlands. Since 2008, consumer preferences have been moving away from large size, weight and power whereby car buyers were offsetting more than 50% of the potential CO₂ reduction from technological advances. From 2008 to 2011 consumer choices not only ceased to offset a large share of the technological advances, but contributed more than an additional 30% to CO₂ reductions. Had consumer preferences not decoupled from the historical upward trend, the Dutch sales-weighted average CO₂ emissions of new passenger cars would have been 139 g/km rather than the 126 grams CO₂ per km in 2011.     

Estimation of nitrogen oxides emissions from petrol and diesel passenger cars by means of on-board monitoring: Effect of vehicle speed,vehicle technology,engine type on emission rates

NO_X emission rates of 13 petrol and 3 diesel passenger cars as a function of average speed from 10 to 120 km/h, emission class (pre-Euro 1 – Euro 5), engine type were investigated by on-board monitoring on roads and highways of St. Petersburg using a portative Testo XXL 300 gas analyzer. The highest level of NO_X emission 0.5–2.5 g/km was inherent to old pre-Euro 1 petrol cars without a catalytic converter. NO_X emissions rates of Euro 1 and Euro 2 petrol cars changed within 0.15–0.9 g/km, Euro 3 – 0.015–0.27 g/km, Euro 4 – 0.013–0.1 g/km, Euro 5 – 0.002–0.043 g/km. Euro 3 – Euro 4 petrol cars generally satisfied corresponding NO_X Emission Standards (ES), except cold-start period, Euro 5 petrol cars did not exceed ES. Warmed, stabilized engines of Euro 3 – Euro 5 petrol cars showed 5–10 times lower NO_X emission rates than corresponding ES in the range of speed from 20 to 90 km/h. NO_X emission rates of diesel Euro 3 and Euro 4 cars varied from 0.45 to 1.1 g/km and from 0.31 to 1.1 g/km, respectively. Two examined diesel Euro 3 and one Euro 4 passenger vehicles did not satisfy NO_X ES at real use. Euro 3 diesel cars showed 28.9 times higher NO_X emissions than Euro 3 petrol cars and Euro 4 diesel car demonstrated 17.6 times higher NO_X emissions than Euro 4 petrol cars at warmed and stabilized engine at a cruise speed ranging from 30 to 60 km/h.     

Ultrafine particle infiltration into passenger vehicles. Part II: Model analysis

Experimental studies showed that infiltration and passive ventilation are important air exchange mechanisms inside vehicles but previous mathematical models did not consider either one. In this study, we incorporated infiltration and passive ventilation to advance the existing mathematical models and evaluated how different transport mechanisms affect passenger exposures at increasing speeds. Infiltration was formulated using Bernoulli’s equation and passive ventilation was derived empirically. The new model describes ultrafine particle (UFP) and carbon dioxide (CO₂) transport for a wide range of driving speed under any ventilation conditions. Unlike statistical models, this mathematical model can also provide vehicle-specific and transport mechanism-specific information. The model predictions were in a good agreement with data collected from 10 different vehicle models with an average discrepancy of less than 16% for UFPs and less than 3% for CO₂. Under outdoor air (OA) mode, when the fan is off, the model simulation showed that the infiltration and passive ventilation can substantially increase the UFP I/O (in-cabin/on-road concentrations) ratio from 0.15 at 0 km/h to 0.57 at 130 km/h. At medium fan setting, mechanical ventilation dominates and UFP I/O stays at 0.58 regardless of driving speed. Under recirculation (RC) mode, infiltration increases and the RC-mode filtration only removed 44% and 69% of the infiltrated particles at the lowest and medium fan settings, respectively. Model simulations under OA mode show that infiltration starts to occur above 115 km/h with the lowest fan setting; whereas, medium and higher fan settings prevent infiltration up to 145 km/h.     

Effects of e-bikes on bicycle use and mode share

In Norway, as in many countries, a political goal is to increase bicycle use, and the e-bike is promising in this respect. However, concerns have been raised about mode-share effects. It has been argued that if the e-bike’s only function is in cycling becoming cycling with electric assistance, there would be no benefit to either the environment or public health. Little is yet known about the use of the e-bike, or of its potential in reducing motorized travel. In the current study, 66 randomly selected participants were given an e-bike to use for a limited period of time and the results compared with those of a control group (N = 160). E-bike cycling trips increased from 0.9 to 1.4 per day, distance from 4.8 km to 10.3 km and, as a share of all transport, from 28% to 48%, whereas with the control group there was no increase in cycling. The effect of the e-bike increased with time, indicating a learning effect among users, and was greater for female than for male cyclists. There were no differences with age. Overall, the results suggest that the e-bike is indeed practical for everyday travel.     

Railway transportation as a source of soil pollution

Surface soil (0–10 cm) samples from 60 sampling sites along the length of railway tracks on the territory of Srem (the western part of the Autonomous Province of Vojvodina, itself part of Serbia) were collected and analyzed for seven polychlorinated biphenyls (PCBs) and ten heavy metals in order to see how the distance from the railroad affects the concentration of some organic and inorganic pollutants in the soil. Samples were taken at a distance of 0.03–4.19 km from the railway. For the soil extraction was used USEPA 3540S method. The extracts were purified on a silica-gel column (USEPA 3630C). The analysis of the extracts was performed by gas chromatography with tandem mass spectrometry. PCBs were not detected only at two locations. Mean total concentration of PCBs for all other sampling locations was 0.0043 ppm dry weight (dw) with a range of 0.0005–0.0227 ppm dw. According to values of Nemerow pollution index Cu, Co, Zn and Ni were the most ubiquitous heavy metals in the area near railroad. Based on these results, it can be said that railway transport is a potential source of PCBs and some heavy metals.     

The effects of physical activity on greenhouse gas emissions for common transport modes in European countries

This paper applies a life cycle methodology to estimate activity-related contributions of transport modes to GHG emissions. The methodology uses national input–output tables, environmental accounts, household budget data and nutritional data to derive food-sector GHG coefficients of consumption for ten European countries. The food energy requirements for each mode of transport are estimated taking account of the modal activity level and energy requirements. Typical national food energy-related emissions for walking, cycling, and driving ranged from 25.6 to 77.3 gCO₂-eq/pass.km, 10.4–31.4 gCO₂-eq/pass.km and 1.7–5.2 gCO₂-eq/pass.km; passenger transport was found to result in no food-related emissions above those for a resting individual. Emissions vary between countries depending on the emissions intensities of their energy sectors as well as food prices and average body weights. A life cycle assessment of modal emissions in the UK is undertaken using the food-energy emissions intensities estimated and car travel was found to have the highest emissions intensity, followed by bus, cycling and walking.     

Volume and GHG emissions of long-distance travelling by Western Europeans

It is generally recognised that long distance travelling accounts for a significant part of the mileage of person travel. However, estimates have been hardly made. The paper estimates volume and GHG emissions of long-distance travel by Western Europeans. The analysis is predominantly based on data of the DATELINE project, the only EU-wide survey on long-distance travelling, conducted in 2001 and 2002. Some studies demonstrate that DATELINE suffers from serious underreporting of journeys. We analysed the causes for underreporting and developed expansion factors that correct for that. These gave the opportunity to estimate long-distance travel volumes and related GHG emissions in 2001/2002. Next an update to 2013 is made using statistics on the development of tourist travel and patronage of long-distance modes. Defining long distance ⩾100 km crow-fly, the estimates per capita in the Western European countries in 2013 are 7.5 journeys (defined as round-trips), 8600 km, and 1300 kg greenhouse gasses. The estimated total GHG emissions of long-distance travelling is 520 megaton. In the Netherlands and Flanders, countries where data on short-distance travelling were available, long-distance travelling accounts for 45% of the mileage and nearly 50% of the GHG emissions of all person transport. Long-distance travelling is growing and is expected to continue to grow, particularly by air. The GHG emissions are expected to grow as well, though to a smaller extent. Because short-distance travelling is stagnating, the shares of long distance travelling in both mileage and GHG emissions are likely to increase.     

Are multi-car households better suited for battery electric vehicles? – Driving patterns and economics in Sweden and Germany

Battery electric vehicles (BEVs) could reduce CO₂ emissions from the transport sector but their limited electric driving range diminishes their utility to users. The effect of the limited driving range can be reduced in multi-car households where users could choose between a BEV and a conventional car for long-distance travel. However, to what extent the driving patterns of different cars in a multi-car household’s suit the characteristics of a BEV needs further analysis. In this paper we analyse the probability of daily driving above a fixed threshold for conventional cars in current Swedish and German car driving data. We find second cars in multi-car households to require less adaptation and to be better suited for BEV adoption compared to first cars in multi-car households as well as to cars in single-car households. Specifically, the share of second cars that could fulfil all their driving is 20 percentage points higher compared to first cars and cars from single-car households. This result is stable against variation of driving range and of the tolerated number of days requiring adaptation. Furthermore, the range needed to cover all driving needs for about 70% of the vehicles is only 220 km for second cars compared to 390 km for the average car. We can further confirm that second cars have higher market viability from a total cost of ownership perspective. Here, the second cars achieve a 10 percentage points higher market share compared to first cars, and to cars in single-car households for Swedish economic conditions, while for Germany the corresponding figure is 2 percentage points. Our results are important for understanding the market viability of current and near-future BEVs.     

A point card system for public transport utilization in Korea

This study analyzes consumer preferences for a new incentive program based on a point card to promote green consumption; the study also examines the program’s impact on bus utilization in South Korea. An ex-ante analysis was conducted to examine how consumer behavior can be modified based on varying incentive levels of the point card system. In addition, the effect of the system on consumers’ public transport utilization and resulting CO₂ emissions reductions are analyzed. The adoption probability of the point card is forecast at about 93%, and annual CO₂ emissions are forecast to decrease by 610 kt CO₂.     

The environmental effects of changing speed limits: A quantile regression approach

Two speed management policies were implemented in the metropolitan area of Barcelona aimed at reducing air pollution concentration levels. In 2008, the maximum speed limit was reduced to 80 km/h and, in 2009, a variable speed system was introduced on some metropolitan motorways. This paper evaluates whether such policies have been successful in promoting cleaner air, not only in terms of average pollutant levels but also during high and low pollution episodes. To do so, we use a quantile regression approach for fixed effect panel data, which allows us analyzing different scenarios (beyond the average levels). We find that the variable speed system improves air quality with regard to the two pollutants considered here, being most effective when nitrogen oxide levels are not too low and when particulate matter concentrations are below extremely high levels. However, reducing the maximum speed limit from 120/100 km/h to 80 km/h has no effect – or even a slightly increasing effect – on the two pollutants, depending on the pollution scenario.     

Thermodynamic,environmental and economic effects of diesel and biodiesel fuels on exhaust emissions and nano-particles of a diesel engine

In this study, diesel (JIS#2) and various biodiesel fuels (BDF20, BDF50, BDF100) are used to operate the diesel engine at 100 Nm, 200 Nm and full load; while the engine speed is 1800 rpm. The system is experimentally studied, and the energy, exergy, sustainability, thermoeconomic and exergoeconomic analyses are performed to the system. The Engine Exhaust Particle Sizer is used to measure the size distribution of engine exhaust particle emissions. Also, the data of the exhaust emissions, soot, particle numbers, fuel consumptions, etc. are measured. It is found that (i) most of the exhaust emissions (except NO_x) are directly proportional to the engine load, (ii) maximum CO₂ and NO_x emissions rates are generally determined for the BDF100 biodiesel fuel; while the minimum ones are calculated for the JIS#2 diesel fuel. On the other hand, the maximum CO and HC emissions rates are generally computed for the JIS#2 diesel fuel; while the minimum ones are found for the BDF100 biodiesel fuel, (iii) fuel consumptions from maximum to minimum are BDF100 > BDF50 > BDF20 > JIS#2 at all of the engine loads, (iv) particle concentration of the JIS#2 diesel fuel is higher than the biodiesel fuels, (v) soot concentrations of the JIS#2, BDF20 and BDF50 fuels are directly proportional to the engine load; while the BDF100 is inversely proportional, (vi) system has better energy and exergy efficiency when the engine is operated with the biodiesel fuels (vii) sustainability of the fuels are BDF100 > BDF50 > BDF20 > JIS#2, (viii) thermoeconomic and exergoeconomic parameters rates from maximum to minimum are JIS#2 > BDF20 > BDF50 > BDF100.     

An assessment of gasoline motorcycle emissions performance and understanding their contribution to Tehran air pollution

Motorcycles are the third most common means of transportation in the megacity of Tehran. Hence, measurements of emission factors are essential for Tehran motorcycle fleets. In this study, 60 carburetor motorcycles of various mileages and engine displacement volumes were tested in a chassis dynamometer laboratory according to cold start Euro-3 emissions certification test procedures. For almost all of the tested samples, the average carbon monoxide (CO) emission factors were about seven times higher than the limits for Euro-3 certification. No motorcycle fell within the Euro-3 certification limit on CO emissions. 125 cc engine displacement volume motorcycles, which are dominant in Tehran, have the most total unburned hydrocarbons and CO emission rates, and they have less nitrous oxides (NO_X) emission rates and fuel consumption compared to those of larger engine volume motorcycles. Calculation of fuel-based emission factors and moles of combustion products shows that about 40% of fuel consumed by 125 cc engine volume motorcycles burns to incomplete combustion products. This proportion is lower for larger engine volume motorcycles. Approximation of relative air–fuel ratio results shows very rich combustion in selected motorcycles. Using a carburetor fuel supply system, low engine compression ratio, aging, and no catalyst could be reasons for high emission rates. These reasons could possibly result in high ultrafine particles emission rates from motorcycles. Comparison of total motorcycle pollutant emissions to that of passenger cars from previous studies in Tehran shows that motorcycles contribute to pollutant much higher than their contribution to the total fleet or total travels.     

The effect of non-recreational transport cycling on use of other transport modes: A cross-sectional on-line survey

Accurate modelling of the health and environmental benefits of non-recreational transport cycling requires information about its effects on the use of other transport modes. Relevant research has not focussed on cycling for transport in a general context (as opposed to bikeshare), nor allowed for multi-modal trips. The influence of trip- and personal-characteristics on whether cycling replaces car-driving have yet to be considered. The present study aimed to address these research gaps. An on-line cross-sectional survey was completed by 1525 Australians who cycle for transport at least once per week. For the most recent trip completed (at least partly) by bicycle participants provided trip distance, and percentage travelled by car, public transport (PT), and walking. They also provided the percentage travelled by each mode for the same trip before taking up transport cycling; and a hypothetical future trip when riding is not possible. Compared to the same trip before, fifty percent of recent trips reduced car use, and around 1/3 eliminated a 100%-car trip. Reduced car use was significantly less likely for trips under 7.5 km, commuting, females, respondents under 55, and regular cyclists. Reduced car use was less likely for respondents who started riding because it is flexible, and more likely for those who started riding to avoid parking. Car-use was reduced by an average of 6.2 km per trip, and each bicycle-km cycled replaced 0.5 car-km. Participants report that since taking up cycling, even when they cannot use their bike, they use cars less and use PT more compared to before they took up cycling. Results suggest that previous studies underestimated the extent to which transport cycling replaces car travel, and highlights trip types and population groups to target with cycling promotion strategies. Information about the per-trip and per-bicycle-km replacement of car, PT and walking may be used for more accurate estimation of the benefits of transport cycling than has hitherto been possible.     

The future mobility of the world population

On average a person spends 1.1 h per day traveling and devotes a predictable fraction of income to travel. We show that these time and money budgets are stable over space and time and can be used for projecting future levels of mobility and transport mode. The fixed travel money budget requires that mobility rises nearly in proportion with income. Covering greater distances within the same fixed travel time budget requires that travelers shift to faster modes of transport. The choice of future transport modes is also constrained by path dependence because transport infrastructures change only slowly. In addition, demand for low-speed public transport is partially determined by urban population densities and land-use characteristics. We present a model that incorporates these constraints, which we use for projecting traffic volume and the share of the major motorized modes of transport—automobiles, buses, trains and high speed transport (mainly aircraft)—for 11 regions and the world through 2050. We project that by 2050 the average world citizen will travel as many kilometers as the average West European in 1990. The average American's mobility will rise by a factor of 2.6 by 2050, to 58,000 km/year. The average Indian travels 6000 km/year by 2050, comparable with West European levels in the early 1970s. Today, world citizens move 23 billion km in total; by 2050 that figure grows to 105 billion.     

How wide should be the adjacent area to an urban motorway to prevent potential health impacts from traffic emissions?

In recent years, several studies show that people who live, work or attend school near the main roadways have an increased incidence and severity of health problems that may be related with traffic emissions of air pollutants. The concentrations of near-road atmospheric pollutants vary depending on traffic patterns, environmental conditions, topography and the presence of roadside structures. In this study, the vertical and horizontal variation of nitrogen dioxide (NO₂) and benzene (C₆H₆) concentration along a major city ring motorway were analysed. The main goal of this study is to try to establish a distance from this urban motorway considered “safe” concerning the air pollutants human heath limit values and to study the influence of the different forcing factors of the near road air pollutants transport and dispersion. Statistic significant differences (p = 0.001, Kruskal–Wallis test) were observed between sub-domains for NO₂ representing different conditions of traffic emission and pollutants dispersion, but not for C₆H₆ (p = 0.335). Results also suggest significant lower concentrations recorded at 100 m away from roadway than at the roadside for all campaigns (p < 0.016 (NO₂) and p < 0.036 (C₆H₆), Mann–Whitney test). In order to have a “safe” life in homes located near motorways, the outdoor concentrations of NO₂ must not exceed 44–60.0 μg m⁻³ and C₆H₆ must not exceed 1.4–3.3 μg m⁻³. However, at 100 m away from roadway, 81.8% of NO₂ receptors exceed the annual limit value of human health protection (40 μg m⁻³) and at the roadside this value goes up to 95.5%. These findings suggest that the safe distance to an urban motorway roadside should be more at least 100 m. This distance should be further studied before being used as a reference to develop articulated urban mobility and planning policies.     

Validating and improving public transport origin–destination estimation algorithm using smart card fare data

Smart card data are increasingly used for transit network planning, passengers’ behaviour analysis and network demand forecasting. Public transport origin–destination (O–D) estimation is a significant product of processing smart card data. In recent years, various O–D estimation methods using the trip-chaining approach have attracted much attention from both researchers and practitioners. However, the validity of these estimation methods has not been extensively investigated. This is mainly because these datasets usually lack data about passengers’ alighting, as passengers are often required to tap their smart cards only when boarding a public transport service. Thus, this paper has two main objectives. First, the paper reports on the implementation and validation of the existing O–D estimation method using the unique smart card dataset of the South-East Queensland public transport network which includes data on both boarding stops and alighting stops. Second, the paper improves the O–D estimation algorithm and empirically examines these improvements, relying on this unique dataset. The evaluation of the last destination assumption of the trip-chaining method shows a significant negative impact on the matching results of the differences between actual boarding/alighting times and the public transport schedules. The proposed changes to the algorithm improve the average distance between the actual and estimated alighting stops, as this distance is reduced from 806 m using the original algorithm to 530 m after applying the suggested improvements.     

Biofuels in aviation: Fuel demand and CO2 emissions evolution in Europe toward 2030

This article presents the results of a scenario-based study carried out at the European Commission’s Joint Research Centre aimed at analyzing the future growth of aviation, the resulting fuel demand and the deployment of biofuels in the aviation sector in Europe. Three scenarios have been produced based on different input assumptions and leading to different underlying patterns of growth and resulting volumes of traffic. Data for aviation growth and hence fuel demand have been projected on a year by year basis up to 2030, using 2010 as the baseline. Data sources are Eurostat statistics and actual flight information from EUROCONTROL. Relevant variables such as the number of flights, the type of aircrafts, passengers or cargo tonnes and production indicators (RPKs) are used together with fuel consumption and CO₂ emissions data. The target of the European Advanced Biofuels Flightpath to ensure the commercialization and consumption of 2 million tons of sustainably produced paraffinic biofuels in the aviation sector by 2020, has also been taken into account. Results regarding CO₂ emission projections to 2030, reveal a steady annual increase in the order of 3%, 1% and 4% on average, for the three different scenarios, providing also a good correlation compared to the annual traffic growth rates that are indicated in the three corresponding scenarios. In absolute values, these ratios correspond to the central, the pessimistic and the optimistic scenarios respectively, corresponding to 360 million tonnes CO₂ emissions in 2030, ranging from 271 to 401 million tonnes for the pessimistic and optimistic scenarios, respectively. This article also reports on the supply potential of aviation biofuels (clustered in HEFA/HVOs and biojet) based on the production capacity of facilities around the world and provides an insight on the current and future trends in aviation based on the European and national policies, innovations and state-of-the art technologies that will influence the future of sustainable fuels in aviation.